Titlebook: Machine Learning in Radiation Oncology; Theory and Applicati Issam El Naqa,Ruijiang Li,Martin J. Murphy Book 20151st edition Springer Inter

Adulate

Knowledge-Based Treatment Planningm the treating team of a current pending case. This notion of using prior treatment planning information constitutes the underlying principle of the so-called knowledge-based treatment planning (KBTP). In this chapter, we will discuss KBTP and provide some examples highlighting its current status, t

榮幸

Serenity

節(jié)省

不如樂死去

Treatment Planning Validationand established techniques for detecting errors in radiotherapy. We will discuss the rationale for using machine learning to detect large errors or outliers in radiotherapy treatment plans. As a concrete example, an automated error detection system for radiation treatment plans will be described. Th

積習(xí)難改

Issam El Naqa,Ruijiang Li,Martin J. MurphyProvides a complete overview of the role of machine learning in radiation oncology and medical physics.Covers the use of machine learning in quality assurance, computer-aided detection, image-guided r

半導(dǎo)體

http://image.papertrans.cn/m/image/620700.jpg

口音在加重

健忘癥

安心地散步